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|
Publications of Josiane Zerubia
Result of the query in the list of publications :
173 Conference articles |
92 - Textural Kernel for SVM Classification in Remote Sensing : Application to Forest Fire Detection and Urban Area Extraction.
F. Lafarge and X. Descombes and J. Zerubia. In Proc. IEEE International Conference on Image Processing (ICIP), Genoa, Italy, September 2005.
Keywords : Support Vector Machines, Learning base, Markov Fields, Forest fires, Urban areas.
Copyright : IEEE
@INPROCEEDINGS{lafarge_icip05,
|
| author |
= |
{Lafarge, F. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Textural Kernel for SVM Classification in Remote Sensing : Application to Forest Fire Detection and Urban Area Extraction}, |
| year |
= |
{2005}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{Genoa, Italy}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2005_lafarge_icip05.pdf}, |
| keyword |
= |
{Support Vector Machines, Learning base, Markov Fields, Forest fires, Urban areas} |
| } |
|
93 - Maximum A Posteriori Estimation of Radar Cross Section in SAR Images using the Heavy-Tailed Rayleigh Model.
A. Achim and E.E. Kuruoglu and J. Zerubia. In Proc. European Signal Processing Conference (EUSIPCO), Antalya, Turkey, September 2005.
@INPROCEEDINGS{achim_eusipco_05,
|
| author |
= |
{Achim, A. and Kuruoglu, E.E. and Zerubia, J.}, |
| title |
= |
{Maximum A Posteriori Estimation of Radar Cross Section in SAR Images using the Heavy-Tailed Rayleigh Model}, |
| year |
= |
{2005}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. European Signal Processing Conference (EUSIPCO)}, |
| address |
= |
{Antalya, Turkey}, |
| pdf |
= |
{http://kilyos.ee.bilkent.edu.tr/~signal/defevent/papers/cr1741.pdf}, |
| keyword |
= |
{} |
| } |
|
94 - Texture-adaptive mother wavelet selection for texture analysis.
G.C.K. Abhayaratne and I. H. Jermyn and J. Zerubia. In Proc. IEEE International Conference on Image Processing (ICIP), Genoa, Italy, September 2005.
Keywords : Texture, Wavelet packet, Adaptive, Mother.
@INPROCEEDINGS{abhayaratne_icip05,
|
| author |
= |
{Abhayaratne, G.C.K. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Texture-adaptive mother wavelet selection for texture analysis}, |
| year |
= |
{2005}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{Genoa, Italy}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/Abhayaratne05icip.pdf}, |
| keyword |
= |
{Texture, Wavelet packet, Adaptive, Mother} |
| } |
Abstract :
Classification results obtained using wavelet-based texture analysis techniques vary with the choice of mother wavelet used in the methodology. We discuss the use of mother wavelet filters as parameters in a probabilistic approach to texture analysis based on adaptive biorthogonal wavelet packet bases. The optimal choice for the mother wavelet filters is estimated from the data, in addition to the other model parameters. The model is applied to the classification of single texture images and mosaics of Brodatz textures, the results showing improvement over the performance of standard wavelets for a given filter length. |
|
95 - A Marked Point Process Model for Tree Crown Extraction in Plantations.
G. Perrin and X. Descombes and J. Zerubia. In Proc. IEEE International Conference on Image Processing (ICIP), Genoa, Italy, September 2005.
Keywords : Stochastic geometry, RJMCMC, Tree Crown Extraction, Object extraction, Marked point process.
@INPROCEEDINGS{perrin_icip05,
|
| author |
= |
{Perrin, G. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{A Marked Point Process Model for Tree Crown Extraction in Plantations}, |
| year |
= |
{2005}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{Genoa, Italy}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/perrin_icip05.pdf}, |
| ps |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/perrin_icip05.ps.gz}, |
| keyword |
= |
{Stochastic geometry, RJMCMC, Tree Crown Extraction, Object extraction, Marked point process} |
| } |
Abstract :
This work presents a framework to extract tree crowns from remotely sensed data, especially in plantation images, using stochastic geometry. We aim at finding the tree top positions, and the tree crown diameter distribution. Our approach consists in considering that these images are some realizations of a marked point process. First we model the tree plantation as a configuration of an unknown number of ellipses. Then, a Bayesian energy is defined, containing both a prior energy which incorporates the prior knowledge of the plantation geometric properties, and a likelihood which fits the objects to the data. Eventually, we estimate the global minimum of this energy using Reversible Jump Markov Chain Monte Carlo dynamics and a simulated annealing scheme. We present results on optical aerial images of poplars provided by IFN. |
|
96 - Shape Moments for Region-Based Active Contours.
P. Horvath and A. Bhattacharya and I. H. Jermyn and J. Zerubia and Z. Kato. In Proc. Hungarian-Austrian Conference on Image Processing and Pattern Recognition, Szeged, Hungary, May 2005.
@INPROCEEDINGS{horvath_hacippr05,
|
| author |
= |
{Horvath, P. and Bhattacharya, A. and Jermyn, I. H. and Zerubia, J. and Kato, Z.}, |
| title |
= |
{Shape Moments for Region-Based Active Contours}, |
| year |
= |
{2005}, |
| month |
= |
{May}, |
| booktitle |
= |
{Proc. Hungarian-Austrian Conference on Image Processing and Pattern Recognition}, |
| address |
= |
{Szeged, Hungary}, |
| url |
= |
{http://vision.vein.hu/HACIPPR/}, |
| keyword |
= |
{} |
| } |
|
97 - A Restoration Method for Confocal Microscopy Using Complex Wavelet Transform.
G. Pons Bernad and L. Blanc-Féraud and J. Zerubia. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Philadelphia, Pennsylvania, USA, March 2005.
@INPROCEEDINGS{pons_icassp2005,
|
| author |
= |
{Pons Bernad, G. and Blanc-Féraud, L. and Zerubia, J.}, |
| title |
= |
{A Restoration Method for Confocal Microscopy Using Complex Wavelet Transform}, |
| year |
= |
{2005}, |
| month |
= |
{March}, |
| booktitle |
= |
{Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, |
| address |
= |
{Philadelphia, Pennsylvania, USA}, |
| pdf |
= |
{http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=1415481}, |
| keyword |
= |
{} |
| } |
Abstract :
Confocal laser scanning microscopy is a powerful and increasingly popular technique for 3D imaging of biological specimens. However the acquired images are degraded by blur from out-of-focus light and Poisson noise due to photon-limited detection. Several deconvolution and/or denoising methods have been proposed to reduce these degradations.Here we propose a wavelet denoising method, which turns out to be very effective for three-dimensional confocal images. To obtain a translation and rotation invariant algorithm, we have developped the 3D Complex Wavelet Transform introduced by N. Kingsbury. These wavelets allow moreover a better directional selectivity of the wavelet coefficients. We show on simulated and real biological data the good performances of this algorithm. |
|
98 - Multimodal statistics of adaptive wavelet packet coefficients: experimental evidence and theory.
R. Cossu and I. H. Jermyn and J. Zerubia. In Proc. Physics in Signal and Image Processing, Toulouse, France, January 2005.
Keywords : Bimodal, Statistics, Wavelet packet, Adaptive, Texture.
@INPROCEEDINGS{cossu_psip05,
|
| author |
= |
{Cossu, R. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Multimodal statistics of adaptive wavelet packet coefficients: experimental evidence and theory}, |
| year |
= |
{2005}, |
| month |
= |
{January}, |
| booktitle |
= |
{Proc. Physics in Signal and Image Processing}, |
| address |
= |
{Toulouse, France}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/Cossu05psip.pdf}, |
| keyword |
= |
{Bimodal, Statistics, Wavelet packet, Adaptive, Texture} |
| } |
Abstract :
In recent work, it was noted that although the subband histograms
for standard wavelet coefcients take on a generalized
Gaussian form, this is no longer true for wavelet packet
bases adapted to a given texture. Instead, three types of subband
statistics are observed: Gaussian, generalized Gaussian,
and interestingly, in some subbands, bi- or multi-modal histograms.
Motivated by this observation, we provide additional
experimental conrmation of the existence of multimodal
subbands, and provide a theoretical explanation for
their occurrence. The results reveal the connection of such
subbands with the characteristic structure in a texture, and
thus confirm the importance of such subbands for image modelling
and applications. |
|
99 - Texture discrimination using multimodal wavelet packet subbands.
R. Cossu and I. H. Jermyn and J. Zerubia. In Proc. IEEE International Conference on Image Processing (ICIP), Singapore, October 2004.
Keywords : Bimodal, Adaptive, probabilistic, Wavelet packet, Texture.
@INPROCEEDINGS{cossu_icip04,
|
| author |
= |
{Cossu, R. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Texture discrimination using multimodal wavelet packet subbands}, |
| year |
= |
{2004}, |
| month |
= |
{October}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{Singapore}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/Cossu04icip.pdf}, |
| keyword |
= |
{Bimodal, Adaptive, probabilistic, Wavelet packet, Texture} |
| } |
Abstract :
The subband histograms of wavelet packet bases adapted to individual
texture classes often fail to display the leptokurtotic behaviour
shown by the standard wavelet coefcients of `natural'
images. While many subband histograms remain leptokurtotic
in adaptive bases, some subbands are Gaussian. Most interestingly,
however, some subbands show multimodal behaviour, with
no mode at zero. In this paper, we provide evidence for the existence
of these multimodal subbands and show that they correspond
to narrow frequency bands running throughout images of the texture.
They are thus closely linked to the texture's structure. As
such, they seem likely to possess superior descriptive and discriminative
power as compared to unimodal subbands. We demonstrate
this using both Brodatz and remote sensing images. |
|
100 - Segmentation of remote sensing images by supervised TS-MRF.
G. Poggi and G. Scarpa and J. Zerubia. In Proc. IEEE International Conference on Image Processing (ICIP), Singapore, October 2004.
@INPROCEEDINGS{poggi_icip04,
|
| author |
= |
{Poggi, G. and Scarpa, G. and Zerubia, J.}, |
| title |
= |
{Segmentation of remote sensing images by supervised TS-MRF}, |
| year |
= |
{2004}, |
| month |
= |
{October}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{Singapore}, |
| url |
= |
{http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1421441}, |
| keyword |
= |
{} |
| } |
|
101 - Gap closure in (road) networks using higher-order active contours.
M. Rochery and I. H. Jermyn and J. Zerubia. In Proc. IEEE International Conference on Image Processing (ICIP), Singapore, October 2004.
Keywords : Active contour, Gap closure, Higher-order, Shape, Road network.
@INPROCEEDINGS{Rochery04,
|
| author |
= |
{Rochery, M. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Gap closure in (road) networks using higher-order active contours}, |
| year |
= |
{2004}, |
| month |
= |
{October}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{Singapore}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/rochery_icip04.pdf}, |
| keyword |
= |
{Active contour, Gap closure, Higher-order, Shape, Road network} |
| } |
Abstract :
We present a new model for the extraction of networks from images in the presence of occlusions. Such occlusions cause gaps in the extracted network that need to be closed. Using higher-order active contours, which allow the incorporation of sophisticated geometric information, we introduce a new, non-local, `gap closure' force that causes pairs of network extremities that are close together to extend towards one another and join, thus closing the gap
between them. We demonstrate the benefits of the model using the problem of road network extraction, presenting results on aerial images. |
|
102 - Texture analysis using adaptative biorthogonal wavelet packets.
G.C.K. Abhayaratne and I. H. Jermyn and J. Zerubia. In Proc. IEEE International Conference on Image Processing (ICIP), Singapore, October 2004.
Keywords : Adaptive, Wavelet packet, Biorthogonal, Texture, Statistics.
@INPROCEEDINGS{Abhayratne_icip04,
|
| author |
= |
{Abhayaratne, G.C.K. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Texture analysis using adaptative biorthogonal wavelet packets}, |
| year |
= |
{2004}, |
| month |
= |
{October}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{Singapore}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/Abhayaratne04icip.pdf}, |
| keyword |
= |
{Adaptive, Wavelet packet, Biorthogonal, Texture, Statistics} |
| } |
Abstract :
We discuss the use of adaptive biorthogonal wavelet packet bases
in a probabilistic approach to texture analysis, thus combining the
advantages of biorthogonal wavelets (FIR, linear phase) with those
of a coherent texture model. The computation of the probability
uses both the primal and dual coefcients of the adapted biorthogonal
wavelet packet basis. The computation of the biorthogonal
wavelet packet coefcients is done using a lifting scheme, which
is very efficient. The model is applied to the classification of mosaics
of Brodatz textures, the results showing improvement over
the performance of the corresponding orthogonal wavelets. |
|
103 - Unsupervised line network extraction from remotely sensed images by polyline process.
C. Lacoste and X. Descombes and J. Zerubia and N. Baghdadi. In Proc. European Signal Processing Conference (EUSIPCO), University of Technology, Vienna, Austria, September 2004.
@INPROCEEDINGS{lacoste04b,
|
| author |
= |
{Lacoste, C. and Descombes, X. and Zerubia, J. and Baghdadi, N.}, |
| title |
= |
{Unsupervised line network extraction from remotely sensed images by polyline process}, |
| year |
= |
{2004}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. European Signal Processing Conference (EUSIPCO)}, |
| address |
= |
{University of Technology, Vienna, Austria}, |
| url |
= |
{http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7079995}, |
| pdf |
= |
{http://www.eurasip.org/Proceedings/Eusipco/Eusipco2004/defevent/papers/cr1608.pdf}, |
| keyword |
= |
{} |
| } |
|
104 - A Discontinuity detector for building extraction from Digital Elevation Models by stochastic geometry.
M. Ortner and X. Descombes and J. Zerubia. In Proc. European Signal Processing Conference (EUSIPCO), University of Technology, Vienna, Austria, September 2004.
Note : this paper has received a Young Authors award
@INPROCEEDINGS{ortner04b,
|
| author |
= |
{Ortner, M. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{A Discontinuity detector for building extraction from Digital Elevation Models by stochastic geometry}, |
| year |
= |
{2004}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. European Signal Processing Conference (EUSIPCO)}, |
| address |
= |
{University of Technology, Vienna, Austria}, |
| note |
= |
{this paper has received a Young Authors award}, |
| url |
= |
{http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7079720}, |
| keyword |
= |
{} |
| } |
|
105 - SAR amplitude probability density function estimation based on a generalized Gaussian scattering model.
G. Moser and J. Zerubia and S.B. Serpico. In Proc. SPIE Symposium on Remote Sensing, Maspalomas, Gran Canaria, Spain, September 2004.
@INPROCEEDINGS{moser2004a,
|
| author |
= |
{Moser, G. and Zerubia, J. and Serpico, S.B.}, |
| title |
= |
{SAR amplitude probability density function estimation based on a generalized Gaussian scattering model}, |
| year |
= |
{2004}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. SPIE Symposium on Remote Sensing}, |
| address |
= |
{Maspalomas, Gran Canaria, Spain}, |
| url |
= |
{http://dx.doi.org/10.1117/12.567853}, |
| keyword |
= |
{} |
| } |
|
106 - Finite mixture models and stochastic EM for SAR amplitude probability density function estimation based on a dictionary of parametric families.
G. Moser and J. Zerubia and S.B. Serpico. In Proc. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Anchorage , USA, September 2004.
@INPROCEEDINGS{moser2004b,
|
| author |
= |
{Moser, G. and Zerubia, J. and Serpico, S.B.}, |
| title |
= |
{Finite mixture models and stochastic EM for SAR amplitude probability density function estimation based on a dictionary of parametric families}, |
| year |
= |
{2004}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. IEEE International Geoscience and Remote Sensing Symposium (IGARSS)}, |
| address |
= |
{Anchorage , USA}, |
| url |
= |
{http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=1368708}, |
| keyword |
= |
{} |
| } |
|
107 - Tree Crown Extraction using Marked Point Processes.
G. Perrin and X. Descombes and J. Zerubia. In Proc. European Signal Processing Conference (EUSIPCO), University of Technology, Vienna, Austria, September 2004.
Keywords : RJMCMC, Marked point process, Simulated Annealing, Tree Crown Extraction, Object extraction, Stochastic geometry.
@INPROCEEDINGS{perrin04a,
|
| author |
= |
{Perrin, G. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Tree Crown Extraction using Marked Point Processes}, |
| year |
= |
{2004}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. European Signal Processing Conference (EUSIPCO)}, |
| address |
= |
{University of Technology, Vienna, Austria}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/perrin_eusipco2004.pdf}, |
| ps |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/perrin_eusipco2004.ps.gz}, |
| keyword |
= |
{RJMCMC, Marked point process, Simulated Annealing, Tree Crown Extraction, Object extraction, Stochastic geometry} |
| } |
Abstract :
In this paper we aim at extracting tree crowns from remotely sensed images. Our approach is to consider that these images are some realizations of a marked point process. The first step is to define the geometrical objects that design the trees, and the density of the process.
Then, we use a Reversible Jump Markov Chain Monte Carlo dynamics and a simulated annealing to get the maximum a posteriori estimator of the tree crown distribution on the image. Transitions of the Markov chain are managed by some specific proposition kernels.
Results are shown on aerial images of poplars provided by IFN. |
|
108 - A Reversible Jump MCMC sampler for building detection in image processing.
M. Ortner and X. Descombes and J. Zerubia. In Monte Carlo Methods and Quasi-Monte Carlo Methods, series Special Se, Juan les Pins (France), June 2004.
@INPROCEEDINGS{mcmcqmc,
|
| author |
= |
{Ortner, M. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{A Reversible Jump MCMC sampler for building detection in image processing}, |
| year |
= |
{2004}, |
| month |
= |
{June}, |
| booktitle |
= |
{Monte Carlo Methods and Quasi-Monte Carlo Methods}, |
| series |
= |
{Special Se}, |
| address |
= |
{Juan les Pins (France)}, |
| url |
= |
{http://link.springer.com/chapter/10.1007%2F3-540-31186-6_23}, |
| keyword |
= |
{} |
| } |
|
109 - A Bayesian Geometric Model for Line Network Extraction from Satellite Images.
C. Lacoste and X. Descombes and J. Zerubia and N. Baghdadi. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Montreal, Quebec, Canada, May 2004.
@INPROCEEDINGS{lacoste04a,
|
| author |
= |
{Lacoste, C. and Descombes, X. and Zerubia, J. and Baghdadi, N.}, |
| title |
= |
{A Bayesian Geometric Model for Line Network Extraction from Satellite Images}, |
| year |
= |
{2004}, |
| month |
= |
{May}, |
| booktitle |
= |
{Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, |
| address |
= |
{Montreal, Quebec, Canada}, |
| url |
= |
{http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1326607}, |
| keyword |
= |
{} |
| } |
|
110 - Deconvolution in confocal microscopy with total variation regularization.
N. Dey and L. Blanc-Féraud and C. Zimmer and Z. Kam and J.C. Olivo-Marin and J. Zerubia. In Proc. French-Danish Workshop on Spatial Statistics and Image Analysis in Biology (SSIAB), pages 117--120, May 2004.
@INPROCEEDINGS{Dey04b,
|
| author |
= |
{Dey, N. and Blanc-Féraud, L. and Zimmer, C. and Kam, Z. and Olivo-Marin, J.C. and Zerubia, J.}, |
| title |
= |
{Deconvolution in confocal microscopy with total variation regularization}, |
| year |
= |
{2004}, |
| month |
= |
{May}, |
| booktitle |
= |
{Proc. French-Danish Workshop on Spatial Statistics and Image Analysis in Biology (SSIAB)}, |
| pages |
= |
{117--120}, |
| url |
= |
{http://www3.jouy.inra.fr/miaj/public/imaste/ssiab2004/program/abw92/}, |
| keyword |
= |
{} |
| } |
|
111 - Texture analysis using probabilistic models of the unimodal and multimodal statistics of adaptative wavelet packet coefficients.
R. Cossu and I. H. Jermyn and J. Zerubia. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Montreal, Canada, May 2004.
Keywords : Bimodal, Adaptive, Wavelet packet, Texture, Gaussian mixture, Statistics.
@INPROCEEDINGS{cossu04a,
|
| author |
= |
{Cossu, R. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Texture analysis using probabilistic models of the unimodal and multimodal statistics of adaptative wavelet packet coefficients}, |
| year |
= |
{2004}, |
| month |
= |
{May}, |
| booktitle |
= |
{Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, |
| address |
= |
{Montreal, Canada}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/Cossu04icassp.pdf}, |
| keyword |
= |
{Bimodal, Adaptive, Wavelet packet, Texture, Gaussian mixture, Statistics} |
| } |
Abstract :
Although subband histograms of the wavelet coefficients of
natural images possess a characteristic leptokurtotic form,
this is no longer true for wavelet packet bases adapted to
a given texture. Instead, three types of subband statistics
are observed: Gaussian, leptokurtotic, and interestingly, in
some subbands, multimodal histograms. These subbands
are closely linked to the structure of the texture, and guarantee
that the most probable image is not flat. Motivated by
these observations, we propose a probabilistic model that
takes them into account. Adaptive wavelet packet subbands
are modelled as Gaussian, generalized Gaussian, or a constrained
Gaussian mixture. We use a Bayesian methodology,
finding MAP estimates for the adaptive basis, for subband
model selection, and for subband model parameters.
Results confirm the effectiveness of the proposed approach,
and highlight the importance of multimodal subbands for
texture discrimination and modelling. |
|
112 - A deconvolution method for confocal microscopy with total variation regularization.
N. Dey and L. Blanc-Féraud and C. Zimmer and Z. Kam and J.C. Olivo-Marin and J. Zerubia. In Proc. IEEE International Symposium on Biomedical Imaging (ISBI), Arlington, USA, April 2004.
Keywords : 3D confocal microscopy, Poisson deconvolution, total variation regularization.
@INPROCEEDINGS{Dey04a,
|
| author |
= |
{Dey, N. and Blanc-Féraud, L. and Zimmer, C. and Kam, Z. and Olivo-Marin, J.C. and Zerubia, J.}, |
| title |
= |
{A deconvolution method for confocal microscopy with total variation regularization}, |
| year |
= |
{2004}, |
| month |
= |
{April}, |
| booktitle |
= |
{Proc. IEEE International Symposium on Biomedical Imaging (ISBI)}, |
| address |
= |
{Arlington, USA}, |
| pdf |
= |
{http://dx.doi.org/10.1109/ISBI.2004.1398765}, |
| keyword |
= |
{3D confocal microscopy, Poisson deconvolution, total variation regularization} |
| } |
Abstract :
Confocal laser scanning microscopy is a powerful and increasingly popular technique for 3D imaging of biological specimens. However the acquired images are degraded by blur from out-of-focus light and Poisson noise due to photon-limited detection. Several deconvolution methods have been proposed to reduce these degradations, including the Richardson-Lucy algorithm, which computes a maximum likelihood estimation adapted to Poisson statistics. However this method tends to amplify noise if used without regularizing constraint. Here, we propose to combine the Richardson-Lucy algorithm with a regularizing constraint based on total variation, whose smoothing avoids oscillations while preserving edges. We show on simulated images that this constraint improves the deconvolution result both visually and using quantitative measures. |
|
113 - Marked Point Process in Image Analysis : from Context to Geometry.
X. Descombes and F. Kruggel and C. Lacoste and M. Ortner and G. Perrin and J. Zerubia. In International Conference on Spatial Point Process Modelling and its Application (SPPA), Castellon, Spain, 2004.
Keywords : RJMCMC, Object extraction, Marked point process, Stochastic geometry.
@INPROCEEDINGS{geostoch04a,
|
| author |
= |
{Descombes, X. and Kruggel, F. and Lacoste, C. and Ortner, M. and Perrin, G. and Zerubia, J.}, |
| title |
= |
{Marked Point Process in Image Analysis : from Context to Geometry}, |
| year |
= |
{2004}, |
| booktitle |
= |
{International Conference on Spatial Point Process Modelling and its Application (SPPA)}, |
| address |
= |
{Castellon, Spain}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/SPPA_2004.pdf}, |
| ps |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/SPPA_2004.ps.gz}, |
| keyword |
= |
{RJMCMC, Object extraction, Marked point process, Stochastic geometry} |
| } |
Abstract :
We consider the marked point process framework as a natural extension of the Markov random field approach in image analysis. We consider a general model defined by its density allowing us to consider some geometrical constraints on objects and between objects in feature extraction problems. Some examples are derived for small brain lesions detection from MR Images, road network, tree crown and building extraction from remotely sensed images. The results obtained on real data show the relevance of the proposal approach. |
|
114 - Extraction automatique de caricatures de bâtiments sur des Modèles Numériques d'Elèvation.
M. Ortner and X. Descombes and J. Zerubia. In Pixels et Cités, ENSG, Marne la Vallée, France, November 2003.
@INPROCEEDINGS{mathiaspix,
|
| author |
= |
{Ortner, M. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Extraction automatique de caricatures de bâtiments sur des Modèles Numériques d'Elèvation}, |
| year |
= |
{2003}, |
| month |
= |
{November}, |
| booktitle |
= |
{Pixels et Cités}, |
| address |
= |
{ENSG, Marne la Vallée, France}, |
| pdf |
= |
{Articles/PixelsCites2003.pdf}, |
| keyword |
= |
{} |
| } |
|
115 - Un Nouveau Modèle Pour L'extraction de Caricatures de Bâtiments sur Des Modèles Numériques D'Élèvation.
M. Ortner and X. Descombes and J. Zerubia. In Proc. Traitement et Analyse de l'Information - Méthodes et Applications (TAIMA), Hammamet, Tunisia, October 2003.
@INPROCEEDINGS{mathiastaima,
|
| author |
= |
{Ortner, M. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Un Nouveau Modèle Pour L'extraction de Caricatures de Bâtiments sur Des Modèles Numériques D'Élèvation}, |
| year |
= |
{2003}, |
| month |
= |
{October}, |
| booktitle |
= |
{Proc. Traitement et Analyse de l'Information - Méthodes et Applications (TAIMA)}, |
| address |
= |
{Hammamet, Tunisia}, |
| url |
= |
{http://conferences.telecom-bretagne.eu/taima/_2003/}, |
| keyword |
= |
{} |
| } |
|
116 - Wavelet-Based Superresolution in Astronomy.
R. Willett and I. H. Jermyn and R. Nowak and J. Zerubia. In Proc. Astronomical Data Analysis Software and Systems, Strasbourg, France, October 2003.
Keywords : Superresolution, Wavelets, Astronomy.
@INPROCEEDINGS{Willett03,
|
| author |
= |
{Willett, R. and Jermyn, I. H. and Nowak, R. and Zerubia, J.}, |
| title |
= |
{Wavelet-Based Superresolution in Astronomy}, |
| year |
= |
{2003}, |
| month |
= |
{October}, |
| booktitle |
= |
{Proc. Astronomical Data Analysis Software and Systems}, |
| address |
= |
{Strasbourg, France}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/Willett03adass.pdf}, |
| keyword |
= |
{Superresolution, Wavelets, Astronomy} |
| } |
Abstract :
High-resolution astronomical images can be reconstructed
from several blurred and noisy low-resolution images using a computational
process known as superresolution reconstruction. Superresolution
reconstruction is closely related to image deconvolution, except that the
low-resolution images are not registered and their relative translations
and rotations must be estimated in the process. The novelty of our approach
to the superresolution problem is the use of wavelets and related
multiresolution methods within an expectation-maximization reconstruction
process to improve the accuracy and visual quality of the reconstructed
image. Simulations demonstrate the effectiveness of the proposed
method, including its ability to distinguish between tightly grouped stars
with a small set of observations. |
|
117 - Higher Order Active Contours and their Application to the Detection of Line Networks in Satellite Imagery.
M. Rochery and I. H. Jermyn and J. Zerubia. In Proc. IEEE Workshop Variational, Geometric and Level Set Methods in Computer Vision, at ICCV, Nice, France, October 2003.
Keywords : Higher-order, Active contour, Shape, Road network, Segmentation, Prior.
@INPROCEEDINGS{Rochery03a,
|
| author |
= |
{Rochery, M. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Higher Order Active Contours and their Application to the Detection of Line Networks in Satellite Imagery}, |
| year |
= |
{2003}, |
| month |
= |
{October}, |
| booktitle |
= |
{Proc. IEEE Workshop Variational, Geometric and Level Set Methods in Computer Vision}, |
| address |
= |
{at ICCV, Nice, France}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/rochery_vlsm03.pdf}, |
| keyword |
= |
{Higher-order, Active contour, Shape, Road network, Segmentation, Prior} |
| } |
Abstract :
We present a novel method for the incorporation of shape information
into active contour models, and apply it to the extraction
of line networks (e.g. road, water) from satellite imagery.
The method is based on a new class of contour energies.
These energies are quadratic on the space of one-chains
in the image, as opposed to classical energies, which are linear.
They can be expressed as double integrals on the contour,
and thus incorporate non-trivial interactions between
different contour points. The new energies describe families
of contours that share complex geometric properties, without
making reference to any particular shape. Networks fall
into such a family, and to model them we make a particular
choice of quadratic energy whose minima are reticulated.
To optimize the energies, we use a level set approach. The
forces derived from the new energies are non-local however,
thus necessitating an extension of standard level set methods.
Promising experimental results are obtained using real
images. |
|
118 - Texture Analysis: An Adaptive Probabilistic Approach.
K. Brady and I. H. Jermyn and J. Zerubia. In Proc. IEEE International Conference on Image Processing (ICIP), Barcelona, Spain, September 2003.
Keywords : Adaptive, Wavelet packet, Statistics, Texture.
@INPROCEEDINGS{Brady03,
|
| author |
= |
{Brady, K. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Texture Analysis: An Adaptive Probabilistic Approach}, |
| year |
= |
{2003}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{Barcelona, Spain}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/Brady03icip.pdf}, |
| keyword |
= |
{Adaptive, Wavelet packet, Statistics, Texture} |
| } |
Abstract :
Two main issues arise when working in the area of texture
segmentation: the need to describe the texture accurately by
capturing its underlying structure, and the need to perform
analyses on the boundaries of textures. Herein, we tackle
these problems within a consistent probabilistic framework.
Starting from a probability distribution on the space of infinite
images, we generate a distribution on arbitrary finite
regions by marginalization. For a Gaussian distribution, the
computational requirement of diagonalization and the modelling
requirement of adaptivity together lead naturally to
adaptive wavelet packet models that capture the ‘significant
amplitude features’ in the Fourier domain. Undecimated
versions of the wavelet packet transform are used to diagonalize
the Gaussian distribution efficiently, albeit approximately.
We describe the implementation and application of
this approach and present results obtained on several Brodatz
texture mosaics. |
|
119 - Extraction de réseaux linéiques à partir d'images satellitaires par processus Markov objet.
C. Lacoste and X. Descombes and J. Zerubia and N. Baghdadi. In Proc. GRETSI Symposium on Signal and Image Processing, Paris, France, September 2003.
@INPROCEEDINGS{lacosteXDJZNB03,
|
| author |
= |
{Lacoste, C. and Descombes, X. and Zerubia, J. and Baghdadi, N.}, |
| title |
= |
{Extraction de réseaux linéiques à partir d'images satellitaires par processus Markov objet}, |
| year |
= |
{2003}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. GRETSI Symposium on Signal and Image Processing}, |
| address |
= |
{Paris, France}, |
| url |
= |
{http://documents.irevues.inist.fr/handle/2042/13529}, |
| keyword |
= |
{} |
| } |
|
120 - Road Network Extraction in Remote Sensing by a Markov Object Process.
C. Lacoste and X. Descombes and J. Zerubia. In Proc. IEEE International Conference on Image Processing (ICIP), Barcelona, Spain, September 2003.
@INPROCEEDINGS{lacosteXDJZ03,
|
| author |
= |
{Lacoste, C. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Road Network Extraction in Remote Sensing by a Markov Object Process}, |
| year |
= |
{2003}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{Barcelona, Spain}, |
| url |
= |
{http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1247420}, |
| keyword |
= |
{} |
| } |
|
121 - Étude D'une Nouvelle Classe de Contours Actifs Pour la Détection de Routes Dans Des Images de Télédétection.
M. Rochery and I. H. Jermyn and J. Zerubia. In Proc. GRETSI Symposium on Signal and Image Processing, Paris, France, September 2003.
@INPROCEEDINGS{Rochery03,
|
| author |
= |
{Rochery, M. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Étude D'une Nouvelle Classe de Contours Actifs Pour la Détection de Routes Dans Des Images de Télédétection}, |
| year |
= |
{2003}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. GRETSI Symposium on Signal and Image Processing}, |
| address |
= |
{Paris, France}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/rochery_gretsi03.pdf}, |
| keyword |
= |
{} |
| } |
|
122 - Adaptive Probabilistic Models of Wavelet Packets for the Analysis and Segmentation of Textured Remote Sensing Images.
K. Brady and I. H. Jermyn and J. Zerubia. In Proc. British Machine Vision Conference (BMVC), Norwich, U. K., September 2003.
Keywords : probabilistic, Adaptive, wavelet, Texture.
@INPROCEEDINGS{Brady03a,
|
| author |
= |
{Brady, K. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Adaptive Probabilistic Models of Wavelet Packets for the Analysis and Segmentation of Textured Remote Sensing Images}, |
| year |
= |
{2003}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. British Machine Vision Conference (BMVC)}, |
| address |
= |
{Norwich, U. K.}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/Brady03bmvc.pdf}, |
| keyword |
= |
{probabilistic, Adaptive, wavelet, Texture} |
| } |
Abstract :
Remote sensing imagery plays an important role in many elds. It has
become an invaluable tool for diverse applications ranging from cartography
to ecosystem management. In many of the images processed in these types
of applications, semantic entities in the scene are correlated with textures
in the image. In this paper, we propose a new method of analysing such
textures based on adaptive probabilistic models of wavelet packets. Our approach
adapts to the principal periodicities present in the textures, and can
capture long-range correlations while preserving the independence of the
wavelet packet coefcients. This technique has been applied to several remote
sensing images, the results of which are presented. |
|
123 - Natural image modeling using complex wavelets.
A. Jalobeanu and L. Blanc-Féraud and J. Zerubia. In Proc. SPIE Conference on Wavelets, Vol. 5207, San Diego, August 2003.
@INPROCEEDINGS{Jalobfjz,
|
| author |
= |
{Jalobeanu, A. and Blanc-Féraud, L. and Zerubia, J.}, |
| title |
= |
{Natural image modeling using complex wavelets}, |
| year |
= |
{2003}, |
| month |
= |
{August}, |
| booktitle |
= |
{Proc. SPIE Conference on Wavelets}, |
| volume |
= |
{5207}, |
| address |
= |
{San Diego}, |
| url |
= |
{http://spie.org/Publications/Proceedings/Paper/10.1117/12.507945}, |
| keyword |
= |
{} |
| } |
|
124 - Remotely sensed image segmentation using an object point process.
S. Drot and H. Le Men and X. Descombes and J. Zerubia. In Proc. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Toulouse, France, July 2003.
@INPROCEEDINGS{drot,
|
| author |
= |
{Drot, S. and Le Men, H. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Remotely sensed image segmentation using an object point process}, |
| year |
= |
{2003}, |
| month |
= |
{July}, |
| booktitle |
= |
{Proc. IEEE International Geoscience and Remote Sensing Symposium (IGARSS)}, |
| address |
= |
{Toulouse, France}, |
| url |
= |
{http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1294331}, |
| keyword |
= |
{} |
| } |
|
125 - Urban Scene Rendering using Object Description.
F. Cerdat and X. Descombes and J. Zerubia. In Proc. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Toulouse, France, July 2003.
@INPROCEEDINGS{fcerdat,
|
| author |
= |
{Cerdat, F. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Urban Scene Rendering using Object Description}, |
| year |
= |
{2003}, |
| month |
= |
{July}, |
| booktitle |
= |
{Proc. IEEE International Geoscience and Remote Sensing Symposium (IGARSS)}, |
| address |
= |
{Toulouse, France}, |
| url |
= |
{http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1293679}, |
| keyword |
= |
{} |
| } |
|
126 - Building Extraction from Digital Elevation Model..
M. Ortner and X. Descombes and J. Zerubia. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Honk Kong, 2003.
@INPROCEEDINGS{mathiasicassp,
|
| author |
= |
{Ortner, M. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Building Extraction from Digital Elevation Model.}, |
| year |
= |
{2003}, |
| booktitle |
= |
{Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, |
| address |
= |
{Honk Kong}, |
| url |
= |
{http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1199477}, |
| keyword |
= |
{} |
| } |
|
127 - Fusion of Radiometry and Textural Information for SIRC Image Classification.
O. Viveros-Cancino and X. Descombes and J. Zerubia and N. Baghdadi. In Proc. IEEE International Conference on Image Processing (ICIP), Rochester, USA, September 2002.
@INPROCEEDINGS{oscarbaghdadi,
|
| author |
= |
{Viveros-Cancino, O. and Descombes, X. and Zerubia, J. and Baghdadi, N.}, |
| title |
= |
{Fusion of Radiometry and Textural Information for SIRC Image Classification}, |
| year |
= |
{2002}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{Rochester, USA}, |
| url |
= |
{http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1038916}, |
| keyword |
= |
{} |
| } |
|
128 - Satellite and aerial image deconvolution using an EM method with complex wavelets.
A. Jalobeanu and R. Nowak and J. Zerubia and M. Figueiredo. In Proc. IEEE International Conference on Image Processing (ICIP), Rochester, USA, September 2002.
@INPROCEEDINGS{nowakjalojz,
|
| author |
= |
{Jalobeanu, A. and Nowak, R. and Zerubia, J. and Figueiredo, M.}, |
| title |
= |
{Satellite and aerial image deconvolution using an EM method with complex wavelets}, |
| year |
= |
{2002}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{Rochester, USA}, |
| url |
= |
{http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1038028}, |
| keyword |
= |
{} |
| } |
|
129 - Image processing for high resolution satellite and aerial data.
J. Zerubia. In Proc. European Signal Processing Conference (EUSIPCO), Toulouse, France, September 2002.
@INPROCEEDINGS{jzEusipco,
|
| author |
= |
{Zerubia, J.}, |
| title |
= |
{Image processing for high resolution satellite and aerial data}, |
| year |
= |
{2002}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. European Signal Processing Conference (EUSIPCO)}, |
| address |
= |
{Toulouse, France}, |
| url |
= |
{http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7072252}, |
| keyword |
= |
{} |
| } |
|
130 - Unsupervised segmentation of textured satellite and aerial images with Bayesian methods.
S. Wilson and J. Zerubia. In Proc. European Signal Processing Conference (EUSIPCO), Toulouse, France, September 2002.
@INPROCEEDINGS{wilsonjz,
|
| author |
= |
{Wilson, S. and Zerubia, J.}, |
| title |
= |
{Unsupervised segmentation of textured satellite and aerial images with Bayesian methods}, |
| year |
= |
{2002}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. European Signal Processing Conference (EUSIPCO)}, |
| address |
= |
{Toulouse, France}, |
| url |
= |
{http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7071914}, |
| keyword |
= |
{} |
| } |
|
131 - A Gauss-Markov Model for Hyperspectral Texture Analysis of Urban Areas.
G. Rellier and X. Descombes and J. Zerubia and F. Falzon. In Proc. International Conference on Pattern Recognition (ICPR), Québec, Canada, August 2002.
@INPROCEEDINGS{rellierXDfalzon,
|
| author |
= |
{Rellier, G. and Descombes, X. and Zerubia, J. and Falzon, F.}, |
| title |
= |
{A Gauss-Markov Model for Hyperspectral Texture Analysis of Urban Areas}, |
| year |
= |
{2002}, |
| month |
= |
{August}, |
| booktitle |
= |
{Proc. International Conference on Pattern Recognition (ICPR)}, |
| address |
= |
{Québec, Canada}, |
| url |
= |
{http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1044850}, |
| keyword |
= |
{} |
| } |
|
132 - Object Point Processes for Image Segmentation.
S. Drot and X. Descombes and H. Le Men and J. Zerubia. In Proc. International Conference on Pattern Recognition (ICPR), Québec, Canada, August 2002.
@INPROCEEDINGS{drotXD,
|
| author |
= |
{Drot, S. and Descombes, X. and Le Men, H. and Zerubia, J.}, |
| title |
= |
{Object Point Processes for Image Segmentation}, |
| year |
= |
{2002}, |
| month |
= |
{August}, |
| booktitle |
= |
{Proc. International Conference on Pattern Recognition (ICPR)}, |
| address |
= |
{Québec, Canada}, |
| url |
= |
{http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1048453}, |
| keyword |
= |
{} |
| } |
|
133 - Estimation of blur and noise parameters in remote sensing.
A. Jalobeanu and L. Blanc-Féraud and J. Zerubia. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Orlando, USA, May 2002.
@INPROCEEDINGS{jallbfjz,
|
| author |
= |
{Jalobeanu, A. and Blanc-Féraud, L. and Zerubia, J.}, |
| title |
= |
{Estimation of blur and noise parameters in remote sensing}, |
| year |
= |
{2002}, |
| month |
= |
{May}, |
| booktitle |
= |
{Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, |
| address |
= |
{Orlando, USA}, |
| url |
= |
{http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5745429}, |
| keyword |
= |
{} |
| } |
|
134 - Building extraction using a Markov point process.
L. Garcin and X. Descombes and J. Zerubia and H. Le Men. In Proc. IEEE International Conference on Image Processing (ICIP), papier invité, Thessalonique, Grèce, October 2001.
@INPROCEEDINGS{xd01d,
|
| author |
= |
{Garcin, L. and Descombes, X. and Zerubia, J. and Le Men, H.}, |
| title |
= |
{Building extraction using a Markov point process}, |
| year |
= |
{2001}, |
| month |
= |
{October}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{papier invité, Thessalonique, Grèce}, |
| url |
= |
{http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=958555}, |
| keyword |
= |
{} |
| } |
|
135 - Image deconvolution using Hidden Markov Tree modeling of complex wavelet packets.
A. Jalobeanu and N. Kingsbury and J. Zerubia. In Proc. IEEE International Conference on Image Processing (ICIP), Thessalonique, Grèce, October 2001.
@INPROCEEDINGS{aj01b,
|
| author |
= |
{Jalobeanu, A. and Kingsbury, N. and Zerubia, J.}, |
| title |
= |
{Image deconvolution using Hidden Markov Tree modeling of complex wavelet packets}, |
| year |
= |
{2001}, |
| month |
= |
{October}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{Thessalonique, Grèce}, |
| url |
= |
{http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=958988}, |
| keyword |
= |
{} |
| } |
|
136 - Two variational models for multispectral image classification.
C. Samson and L. Blanc-Féraud and G. Aubert and J. Zerubia. In Proc. Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR), Sophia Antipolis, France, September 2001.
@INPROCEEDINGS{lbf01a,
|
| author |
= |
{Samson, C. and Blanc-Féraud, L. and Aubert, G. and Zerubia, J.}, |
| title |
= |
{Two variational models for multispectral image classification}, |
| year |
= |
{2001}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR)}, |
| address |
= |
{Sophia Antipolis, France}, |
| url |
= |
{http://link.springer.com/chapter/10.1007%2F3-540-44745-8_23}, |
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137 - Classification d'image satellitaire superspectrale en zone rurale et périurbaine.
O. Pony and U. Polverini and L. Gautret and J. Zerubia and X. Descombes. In Proc. GRETSI Symposium on Signal and Image Processing, Toulouse, France, September 2001.
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138 - Un modèle markovien gaussien pour l'analyse de texture hyperspectrale en milieu urbain.
G. Rellier and X. Descombes and J. Zerubia and F. Falzon. In Proc. GRETSI Symposium on Signal and Image Processing, Toulouse, France, September 2001.
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139 - Estimation de paramètres instrumentaux en imagerie satellitaire.
A. Jalobeanu and L. Blanc-Féraud and J. Zerubia. In Proc. GRETSI Symposium on Signal and Image Processing, Toulouse, France, September 2001.
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140 - Parameter estimation by a Markov Chain Monte Carlo technique for the Candy-model.
X. Descombes and M.N.M. van Lieshout and R. Stoica and J. Zerubia. In IEEE Workshop on Statistical Signal Processing, papier invité, Singapour, August 2001.
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141 - La poursuite de projection pour la classification d'images hyperspectrales texturées.
G. Rellier and X. Descombes and J. Zerubia and F. Falzon. In Proc. Journées des jeunes chercheurs en vision par ordinateur, Cahors, France, June 2001.
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|
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